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Title: Linear Data Structures: A Comparison of Novice and Expert Teacher Pedagogical Content Knowledge
Pedagogical content knowledge (PCK), which includes knowledge of student understanding and knowledge of instructional strategies to support learning, is a component of teaching expertise that develops over time and with experience. In this poster, I present exploratory work to identify and categorize PCK amongst secondary teachers new to computing. Four teachers participating in a multi-year case study completed a questionnaire where they (a) listed student difficulties with linear data structures and (b) described how they address the topic in their teaching. Using a content analysis approach, I analyzed the quantity and type of responses provided. Since little research exists describing computing PCK, I also compared responses against public data sources gathered from experienced teachers who completed similar tasks. Results show that participants provided more ideas about student difficulties than teaching strategies and they focused equally on difficulties with programming notation and with programming pragmatics and plans. In contrast, the experienced educator list included a wider range of difficulty types. Ideas about teaching strategies focused mostly on presenting information, while the experienced educator list focused mostly on providing problem solving tasks. Unlike participants, the experienced educator list referenced real-life examples as an instructional strategy. Lastly, the responses provided by participants were not simply a subset of the experienced educator list and included unique ideas. On the poster I suggest possible contextual and experiential differences between new and experienced computing teachers that might lead to these differences.  more » « less
Award ID(s):
1348866
NSF-PAR ID:
10353803
Author(s) / Creator(s):
Date Published:
Journal Name:
SIGCSE '19: Proceedings of the 50th ACM Technical Symposium on Computer Science Education
Page Range / eLocation ID:
1273 to 1273
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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